Assessment of a fully automated, high-throughput mammographic density measurement tool for use with processed digital mammograms.

Purpose: The ImageJ model is a recently developed automated breast density measurement tool based on analysis of Cumulus outcomes. It has been validated on digitized film-screen mammograms. In this study, the ImageJ model was assessed on processed full-field digital mammograms and correlated with th...

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Bibliographic Details
Published in:Cancer Causes & Control Vol. 25; no. 8; pp. 1037 - 1044
Main Authors: Couwenberg, A M, Verkooijen, H M, Li, J, Pijnappel, R M, Charaghvandi, K R, Hartman, M, van Gils, C H
Format: research Journal Article
Published: Springer Nature Aug2014
Online Access:View this record in EBSCOhost
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Summary:Purpose: The ImageJ model is a recently developed automated breast density measurement tool based on analysis of Cumulus outcomes. It has been validated on digitized film-screen mammograms. In this study, the ImageJ model was assessed on processed full-field digital mammograms and correlated with the Breast Imaging Reporting and Data System (BI-RADS) density classification. Also, the association with breast cancer risk factors is observed.Methods: Women with mammographies between 2001 and 2011 at the University Medical Center Utrecht, The Netherlands were included. We composed a training set, read with Cumulus, for building the ImageJ model [n = 100 women, 331 images; craniocaudal (CC) and mediolateral oblique (MLO) views, left and right] and a validation set for model assessment and correlation with the BI-RADS classification [n = 530 women, 1,977 images; average of available CC and MLO views, left and right]. Pearson product-moment correlation coefficient was used to compare Cumulus with ImageJ, Spearman correlation coefficient for ImageJ with BI-RADS density, and generalized linear models for association with breast cancer risk factors.Results: The correlation between ImageJ and Cumulus in the training set was 0.90 [95 % confidence interval (CI) 0.86-0.93]. After application to the validation set, we observed a high correlation between ImageJ and the BI-RADS readings (Spearman r = 0.86, 95 % CI 0.84-0.88). Women with higher density were significantly younger, more often premenopausal, had lower parity, more often a benign breast lesion or family history of breast cancer.Conclusions: The ImageJ model can be used on processed digital mammograms. The measurements strongly correlate with Cumulus, the BI-RADS density classification, and breast cancer risk factors.